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Transition to entrainment in downward annular gas-liquid flow: Study through flow control

INTERNATIONAL JOURNAL OF MULTIPHASE flow 2025年 184卷

作者： Cherdantsev, Andrey Isaenkov, Sergey Markovich, Dmitry Kutateladze Inst Thermophys Novosibirsk Russia

Formation of disturbance waves and entrainment of liquid droplets drastically enhances pressure drop and heat and mass transfer in annular flow. Here we investigate the transition to entrainment by analyzing spatiotemporal records of film thickness in the vicinity of the transition border. Two branches of the border: "vertical", with high gas speeds and low liquid flow rates, and "horizontal", with low gas speeds and large liquid flow rates, are analyzed separately. In both cases, low-frequency pulsations of liquid flow rate are applied in attempt to expand the regime area of entrainment and learn more about the transition. It was found that two conditions are necessary for creation of a disturbance wave: strong localized perturbations able to create the initial hump of liquid and enough spare liquid in excess of the viscous sub-layer to fill and maintain this hump. Below the "vertical" branch, the disturbance waves do not occur due to lack of spare liquid. Below the "horizontal" branch, no sources of strong perturbations are present. Both "vertical" and "horizontal" branches can be shifted towards lower values of liquid flow rate and gas speed, respectively, using low-frequency oscillations of liquid flow rate. However, the mechanisms of creating these artificial disturbance waves are different. For "vertical" branch, the pulsations create patches of larger liquid flow rate, where disturbance waves can be created in a "natural" manner. For "horizontal" branch, each pulsation period creates a single disturbance wave, provided that the excitation frequency belongs to appropriate range.

关键词： Annular flow Disturbance waves Entrainment flow control Inlet forcing flow patterns

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A New Self-Healing Green Polymer Gel with Dynamic Networks for flow control in Harsh Reservoirs

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ADVANCED FUNCTIONAL MATERIALS 2025年第17期35卷

作者： Kang, Chuanhong Guo, Jixiang Kiyingi, Wyclif Li, Jiao Xue, Pengcheng China Univ Petr Unconvent Petr Res Inst Beijing 102249 Peoples R China

Hydrogels are widely used in flow control of underground reservoirs, a self-healing in situ cross-linked polymer gel system with a dynamic covalent adaptive network and dynamic disulfide bond is designed and constructed with cystine hydrochloride containing disulfide bond as a green cross-linking agent. The polyacrylamide/cystine system can form a gel at temperatures above 110 degrees C, the dynamic disulfide bonds in the gel network make the hydrogels have excellent toughness and self-healing properties and the maximum toughness value of the self-healing gel is 57.5 MJ m-3, and the self-healing efficiency can reach 88%. At the same time, the storage modulus of the gel can reach more than 2000 Pa with the addition of nano SiO2. The cross-linked gel formulated using formation water is stable at 170 degrees C for more than 270 days. The modulated flooding experiment results show that the new gel system can effectively reduce the water content and increase the recovery rate by 32.2%. At the same time, the formation damage test shows that the average plugging rate of the gel is 95%, and the permeability damage is less than 15%. This new self-healing green gel system can replace existing toxic gel systems and prioritize fluid flow control in harsh reservoir conditions.

关键词： disulfide bond dynamic network flow control polymer gel self-healing green gel

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EFLB-IIoT: Enhanced flow control and Load Balancing Approach for SDN-Enabled Industrial Internet-of-Things

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2025年第6期38卷

作者： Kumar, Santosh Malik, Aruna NIT Jalandhar Dept Comp Sci & Engn Jalandhar Punjab India

Software-defined networks (SDN) provide an efficient network architecture by enhancing global network monitoring and performance through the separation of the control plane from the data plane. In extensive SDN implementations for the Internet-of-Things (IoT), achieving high scalability and reducing controller load necessitates deploying multiple distributed controllers that collaboratively manage the network. Each controller oversees a subset of switches and gathers information about these switches and their interconnections, which can lead to imbalances in link and controller loads. Addressing these imbalances is crucial for improving quality of service (QoS) in SDN-enabled Industrial Internet-of-Things (IIoT) environments. In this paper, we present the NP-hardness of the link and controller load balancing routing (LCLBR) problem within IIoT. To tackle this issue, we propose an enhanced flow control and load balancing approach for SDN-enabled Industrial Internet-of-Things (EFLB-IIoT). EFLB-IIoT is an approximation-based technique that effectively maintains network activity among distributed controllers. Simulation results indicate that our proposed strategy reduces the maximum link load by 76% and the maximum controller response time by 85% compared to existing techniques, demonstrating superior performance over state-of-the-art methods.

关键词： distributed controller flow control load balancing Ryu controller software-defined networks

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Numerical Study of flow control to Increase Vertical Tail Effectiveness of an Aircraft by Tangential Blowing

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INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2025年第2期26卷 785-799页

作者： Taleghani, Arash Shams Hesabi, Ashkan Esfahanian, Vahid Minist Sci Res & Technol Aerosp Res Inst Mahestan StPOB Tehran 14665834 Iran Univ Tehran Dept Aerosp Engn Kish Int Campus Kish Iran Univ Tehran Coll Engn Sch Mech Engn Tehran Iran

This paper aims to utilize blowing as an active flow control technology to enhance the aerodynamic efficiency of an aircraft's vertical tail. A computational method has been developed to increase the aerodynamic performance of the vertical tail (at zero angle of attack and zero side slip conditions) through tangential blowing at Mach 0.2. The use of blowing for increased directional control has the potential to improve airplane performance and reduce fuel consumption. The numerical approach relies on the Reynolds averaged Navier-Stokes formulation for grids. A computational analysis examines three geometry types aimed at enhancing the side force. The initial form, or base state, has no tangential blowing, whereas the second uses tangential blowing from a full span slot and the third applies blowing from a series of discrete slots at the hinge line. In the second scenario, separation is entirely regulated, whereas control for discrete slots is comparatively weaker. The side force increased by 8.5% in the condition where 9.9 kg/s of air was blown through a single slot compared to the base condition. Meanwhile, when air is blown through discrete slots at a mass flow rate of 2.7 kg/s, there is a 4% increase in side force. A comparison of utilizing two methods, one with single slot and the other with discrete slots, reveals that the latter requires 70% less mass flow rate to achieve identical side force as the former.

关键词： flow control Aircraft Tangential blowing Vertical tail Computational fluid dynamics

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Data-driven wind farm flow control and challenges towards field implementation: A review

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2025年 216卷

作者： Goecmen, Tuhfe Liew, Jaime Kadoche, Elie Dimitrov, Nikolay Riva, Riccardo Andersen, Soren Juhl Lio, Alan W. H. Quick, Julian Rethore, Pierre-Elouan Dykes, Katherine Tech Univ Denmark DTU Dept Wind & Energy Syst Frederiksborgvej 399 DK-4000 Roskilde Denmark Tech Univ Denmark DTU Dept Wind & Energy Syst Anker Engelunds Vej 1 DK-2800 Lyngby Denmark TotalEnergies OneTech 2 Pl Jean Millier F-92400 Courbevoie France Nordex SE Langenhorner Chaussee 600 D-2419 Hamburg Germany

Data-driven wind farm flow control (WFFC) is an innovative approach that leverages the collected data and advanced analytics to enhance the performance of wind turbines within wind farms. Its significance lies in its ability to adapt to changing wind and turbine conditions and improve operations, boosting energy yield, extending turbine/component lifetime, and potentially reducing socio-environmental impact and costs, thus supporting the viability and sustainability of wind energy as a renewable power source. This review explores the dynamic field of data-driven WFFC and its challenges towards practical implementation. Building on top of traditional wind farm modelling and model-based control, it details the virtues and limitations of these methods while introducing the concept of data-informed or data-driven flow models that harness data to augment predictive accuracy and control strategies. The analysis then covers the methodologies for power and load surrogates, elucidating the pivotal role of surrogate modelling in enhancing WFFC, and showcasing its value in decision-making and energy optimisation. Furthermore, the growing field of reinforcement learning (RL) is highlighted, showcasing its adaptive potential to revolutionise wind farm control through learning from past interactions. The investigation concludes by identifying key challenges impeding the practical deployment of data-driven WFFC, including data quality concerns, cybersecurity risks, and limitations of the current algorithms. In summary, this comprehensive review presents the ongoing development of data-driven WFFC, emphasising the synergy between traditional methods, surrogate modelling, RL, and the critical challenges to be addressed for successful integration of these methodologies in real-world wind farm operations.

关键词： Wind farm control flow control Wake control Data-driven modelling Surrogate modelling

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Genetically-based active flow control of a circular cylinder wake via synthetic jets

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EXPERIMENTAL THERMAL AND FLUID SCIENCE 2025年 162卷

作者： Scala, Alessandro Paolillo, Gerardo Greco, Carlo Salvatore Astarita, Tommaso Cardone, Gennaro Dept Ind Engn Via Claudio 21 I-80125 Naples Italy

The present work investigates the use of Machine Learning methods for optimizing the control of the wake behind a circular cylinder with the aim of reducing the associated aerodynamic drag using a single synthetic jet located at the rear stagnation point. Initially, a parametric study on sinusoidal shapes is performed to assess the control authority of the synthetic jet and to identify suitable initial configurations for the subsequent optimization study. This optimization leverages gradient-enriched Machine Learning (gMLC), which is based on Linear Genetic Programming, to determine the optimal waveshape for the input driving signal to the synthetic jet actuator, aiming at aerodynamic drag reduction. Machine Learning is thus exploited to overcome limitations inherent to canonical waveshapes. All the experiments are performed at a Reynolds number Re = 1.9 x 104. Four different optimization runs are conducted to study the effect of increasing the complexity of the genetic recombination process and including a power penalty in the cost function on the control effectiveness. The maximum drag reduction is achieved when no penalty for the power consumption is included in the cost function and amounts to 9.77% with respect to the baseline case. The addition of the power penalty results in control laws comparable in both waveshape and performance to the canonical sinusoidal control laws. In the second part of this work, the ML-derived control policies are investigated via hot-wire anemometry and Particle Image Velocimetry (PIV) to understand and characterize the mechanisms responsible for the drag reduction and the control effects on the wake evolution. For this purpose, a modal analysis based on Proper Orthogonal Decomposition is performed to comparatively assess the control laws and evaluate their capability of weakening and mitigating the most energetic flow structures associated with the vortex shedding phenomenon.

关键词： Machine Learning Linear Genetic Programming flow control Drag reduction Particle Image Velocimetry

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Review of Passive flow control Methods for Compressor Linear Cascades

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APPLIED SCIENCES-BASEL 2025年第7期15卷 4040-4040页

作者： Dumitrescu, Oana Prisacariu, Emilia-Georgiana Dragan, Valeriu Romanian Res & Dev Inst Gas Turbines COMOTI Bucharest 061126 Romania

This paper reviews the evolution of flow control methods for bladed linear cascades, focusing on passive techniques like riblets, grooves, vortex generators (VGs), and blade slots, which have proven effective in reducing drag, suppressing flow separation, and enhancing stability. The review outlines key historical developments that have improved flow efficiency and reduced losses in cascades. Bio-inspired designs, including riblets and grooves, help stabilize the boundary layer, reduce loss coefficients, and improve flow turning, which is vital for controlling drag and secondary flow effects. Vortex generators, fences, and slotted wingtips enhance stall margins and suppress corner separation, improving performance under off-design conditions. These methods are optimized based on aerodynamic parameters such as Reynolds number and boundary layer characteristics, offering substantial efficiency gains in high-performance compressors. Advancements in computational tools, like high-fidelity simulations and optimization techniques, have provided deeper insights into complex flow phenomena, including turbulence and vortex dynamics. Despite these advancements, challenges remain in fully optimizing these methods for diverse operating conditions and ensuring their practical application. This review highlights promising strategies for improving flow control efficiency and robustness, contributing to the design of next-generation turbomachinery.

关键词： flow control turbomachinery fluid dynamics passive control

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Separation Performance Enhancement of Gas-Solid Cyclone Separators by flow control and Coupling Physical Fields

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SEPARATION AND PURIFICATION REVIEWS 2025年

作者： Dong, Jipeng Chen, Guanghui Zhang, Pan Li, Jianlong Qingdao Univ Sci & Technol Coll Chem Engn Qingdao 266043 Peoples R China Qingdao Univ Sci & Technol Coll Electromech Engn 99 Songling Rd Qingdao 266069 Peoples R China

Cyclone separators have been widely applied in industrial applications to separate solid particles from fluid suspensions. Despite many advantages, their separation performance often falls short of expectations, especially for smaller particles. Significant efforts have been dedicated to enhancing the performance of cyclones over an extended period. This review aims to provide an overview of these endeavors. The review begins by comparing the characteristics of cyclone separators with different gas-solid flow patterns. This analysis provides a comprehensive understanding of how different flow patterns impact the performance of cyclones. The review then discusses on how flow controls, particularly through secondary flows and preprocessing inlet flow, separation. Furthermore, it offers a critical overview of the coupling of cyclone separators with different physical fields to enhance performance, along with the challenges associated with this approach. Finally, the review summarizes some key findings and outlines the challenges in these areas.

关键词： Cyclone separator flow control secondary flow performance enhancement multi-physics coupling

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Investigation of blowing and suction for turbulent flow control on a transonic airfoil

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INTERNATIONAL JOURNAL OF HEAT AND FLUID flow 2025年 113卷

作者： Frede, A. Gatti, D. Karlsruhe Inst Technol Inst Fluid Mech Kaiserstr 10 DE-76131 Karlsruhe Germany

Active flow control of compressible turbulent boundary layers on airfoils via wall-normal blowing and suction is studied through a comprehensive parametric study. Wall-normal blowing or suction is applied in different positions on either the suction or pressure side of the transonic airfoil RAE2822 and its effect on the aerodynamic efficiency is investigated. The effect of the angle of attack, Mach number, control magnitude, and control position on the result of the active control are discussed. The compressible flow is simulated via Reynolds-averaged Navier-Stokes equations (RANS) with the open-source solver SU2. The inclusive drag as well as a power budget are introduced and calculated to determine the control configurations that decrease the total drag also accounting for the effort to provide and dump the control fluid. The study shows the promising potential of suction on the suction side in the transonic regime where total net drag savings of 16% were achieved in the investigated parameter range. Contrary to previous results, suction leads to a decrease in the total drag, whereas blowing leads to an increase. The appearance of non-linear effects as the shock wave, which is strongly influenced by the active control, contributes to the different performance compared to previous studies, which mostly considered incompressible flows.

关键词： flow control Turbulent boundary layer Transonic flow

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Research on vorticity driven reward for active flow control over airfoil based on deep reinforcement learning

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JOURNAL OF HYDRODYNAMICS 2025年第1期37卷 124-137页

作者： Dong, Xiang-rui You, Sun-yu Wang, Qi Zhu, Jia-hao Jin, Zhi-hao Univ Shanghai Sci & Technol Sch Energy & Power Engn Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Shanghai Key Lab Multiphase Flow & Heat Transfer P Shanghai 200093 Peoples R China

An intelligent flow control on the flow separation over an airfoil under weak turbulent conditions is investigated and solved by deep reinforcement learning (DRL) method. Both single and synthetic jet control at the airfoil angles of attack of 10 degrees, 13 degrees, 15 degrees are compared by training a neural network for closed-loop active flow control strategy based on the soft actor-critic (SAC) algorithm. The training results demonstrate the effectiveness of the deep reinforcement learning-based active flow control method in suppressing the flow separation at high angles of attack, validating its potential in complex flow environments. To improve the stability of the shedding vortex alley over airfoil, a novel reward function considering the vorticity statistics in terms of both vortex and asymmetric shear intensity is first proposed in this work. This vorticity driven reward is demonstrated to perform better in suppressing the rotation and shear intensity and the aerodynamic optimization than the traditional one. Moreover, it can accelerate the convergence speed during the exploration phase. Moreover, it can accelerate the convergence speed during the exploration phase. This study provides valuable insights for future applications of DRL in active flow control under more complex flow conditions.

关键词： Fluid mechanics flow control deep reinforcement learning (DRL) multiple attack angle synthetic jet

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